CN109360606B - A kind of method of low-density SNP genome area Accurate Prediction BSA-seq candidate gene - Google Patents
A kind of method of low-density SNP genome area Accurate Prediction BSA-seq candidate gene Download PDFInfo
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Abstract
The present invention relates to genomic sequencing technique fields, in particular to a kind of method of low-density SNP genome area Accurate Prediction BSA-seq candidate gene, the present invention has the region low-density SNP for BSA-seq near candidate section, pass through the SNP between two parent of the rate of exchange, SNP list is strictly filtered, density regions are found out, corresponding candidate section adds low-density candidate section when being then 95% using confidence interval, annotates using genome annotation website to the gene in candidate region；It to candidate region variant sites functional annotation, obtains there are the gene of the functional variants such as frameshift variant, and the determining gene is candidate gene；Using method of the invention can overcome the disadvantages that as the small region of genome difference and caused by candidate region false positive, obtain really candidate section.
Description
[technical field]
The present invention relates to genomic sequencing technique field, in particular to a kind of low-density SNP genome area Accurate Prediction
The method of BSA-seq candidate gene.
[background technique]
Group's segregation analysis (bulked segregant analysis, BSA) is 1991 by R.W.MICHELMORE
A kind of method for the quick location control objective trait gene applied for the first time on lettuce.Method is to take to have pole in progeny population
The single plant of phenotype is held, its DNA of equivalent pooling forms two ponds DNA, is then marked between parent and two ponds polymorphic
Screening carries out genotyping by the polymorphic marker obtained to filial generation mass screening, the positioning to target gene can be completed,
Without carrying out genotyping in group to each label.With the rise of high pass sequencing technologies, it is based on full genome
The BSA analysis method that group resurveys sequence is widely used in important plant traits positioning, has spies such as " quick, efficient, inexpensive "
Point.The basic ideas of BSA-seq typically refer to select extremists from mapping population, and then mixed in equal amounts sample constitutes two
A pond DNA carries out high-flux sequence to parent and pond, identifies the SNPs shared in parent and two ponds, calculate two mixing
The genotype frequency and its difference of identical variant sites in the pond DNA mark polymorphism between pond with difference to embody, thus real
The positioning of existing candidate gene is however, BSA-seq is deposited relative to the assignments of genes gene mapping technology such as whole-genome association, genetic map
In the disadvantages such as accuracy is low, accuracy is low, how Accurate Prediction is carried out to the candidate gene in the region low-density SNP, is our faces
The problem faced, the false positive for the candidate region more often being be easy to cause in the small region of genome difference.
[summary of the invention]
In view of above content, it is necessary to carry out Accurate Prediction to candidate gene for the small genome area of difference, and mention
For a kind of quick, efficient, cheap prediction technique.
In order to achieve the above objectives, the technical scheme adopted by the invention is that:
A kind of method of low-density SNP genome area Accurate Prediction BSA-seq candidate gene, the method includes as follows
Step:
(1) mix pond: the significant parent of selection target Traits change constructs segregating population, and pole is then selected from segregating population
Several single plants of end phenotype are mixed into the pond DNA of two equivalent respectively；
(2) it extracts DNA: extracting plant genome DNA；
(3) be sequenced: the DNA sample of detecting step (2), it is qualified after by DNA fragmentation, DNA fragmentation is modified, PCR
Amplification constructs sequencing library, is sequenced after library quality inspection is qualified；
(4) it compares: the sequencing reads that step (3) obtain is repositioned into reference on genome, being compared, count,
Calculate the sequencing depth and coverage relative to reference genome；
(5) detection of SNP SNP detection and annotation: is carried out using GATK software；Annotation variation is carried out using software SnpEff
And forecast variation；
(6) SNP-index association analysis: being filtered SNP, carries out frequency difference analysis, SNP-index is calculated
And the distribution of △ SNP-index；
(7) candidate interval analysis: according to the distribution situation of step (6) △ SNP-index, select density regions for candidate
Section annotates candidate section gene using genome annotation website；Functional annotation is carried out to candidate section variant sites,
It finds out there are the gene of the functional variants such as frameshift variant, obtains candidate gene；Candidate gene is carried out using qRT-PCR technology
Verifying.
Further, which is characterized in that the filter criteria of step (6) the SNP filtering is as follows: firstly, having filtered out more
The SNP site of a genotype filters out gene between mixed pond secondly, filtering out SNP site of the reads support less than 4 again
The consistent SNP site of type and recessive mixed pond gene are not from the SNP site of recessive parent.
Further, the calculating of the step (6) calculates relating value using SNP-index method, and uses DISTANCE
Method is fitted △ SNP-index.
Further, step (5) the SNP detection and annotation method are as follows:
Step S1: SNP the and small InDel of sequencing genomes is detected by GATK software tool pack；It is soft by bwa
Part takes mem algorithm to compare the sequencing reads of high quality to reference genome, according to Clean reads in reference genome
Positioning result, use Picard filter redundancy reads；SNP and InDel is carried out using the local haplotype packing algorithm of GATK
Variation detection, the first each self-generating gVCF of each sample, then carry out group joint-genotype and obtain variant sites collection；And it is right
Variation result is filtered to obtain filtered snp list, the filter criteria are as follows: the variation quantity in 5bp window is no more than 2
It is a；The mass value of Phred format is not less than 30；Variation mass value is not less than 2.0 divided by the ratio of overburden depth；All comparisons are extremely
The root mean square of the comparison mass value of reads on the site is not less than 40；FS value is not higher than 60；Other variation filtration parameters use
The specified default value processing of GATK official.
Step S2: obtaining filtered snp list based on step S1, is obtained by the script of customization in male parent pond and mother
It is the site snp between parent that this pond, which has discrepant site, and the distribution density of snp is then counted by sliding window, is customized
Script draw distribution map.
Another object of the present invention further includes application of the above method in plant gene label.
Further, the plant is rice.
Further, the parent of the rice is that Huang Hua is accounted for and Donglan ink rice.
Further, the plant gene is that rice seed peel anthocyanidin synthesizes gene.
Further, the anthocyanidin synthesis gene is LOC_Os01g44260.
The invention has the following beneficial effects:
The present invention has the region low-density SNP for BSA-seq near candidate section, by the SNP between two parent of the rate of exchange,
SNP list is strictly filtered, density regions are found out, corresponding candidate section adds when being then 95% using confidence interval
Upper low-density candidate section annotates the gene in candidate region using genome annotation website；It makes a variation to candidate region
Site functional annotation is obtained there are the gene of the functional variants such as frameshift variant, and the determining gene is candidate gene；Use this
The method of invention can overcome the disadvantages that as the small region of genome difference and caused by candidate region false positive, obtain really candidate
Section.
[Detailed description of the invention]
Fig. 1 is the analysis chart of candidate gene confidence interval of the embodiment of the present invention；
Fig. 2 is the SNP distribution map on genome of the embodiment of the present invention.
[specific embodiment]
All features disclosed in this specification or disclosed all methods or in the process the step of, in addition to mutually exclusive
Feature and/or step other than, can combine in any way.
Any feature disclosed in this specification (including any accessory claim, abstract), unless specifically stated, each
Feature is an example in a series of equivalent or similar characteristics.
Embodiment:
A kind of method for present embodiments providing low-density SNP genome area Accurate Prediction BSA-seq candidate gene, should
Method and step is as follows:
(1) mixed pond: the significant parent of selection target Traits change " Huang Huazhan × Donglan ink rice " building segregating population, then from
The extreme 30-50 single plant of objective trait phenotype is chosen in segregating population, be mixed into respectively two ponds DNA (DNA pools) into
Row sequencing；
(2) it extracts DNA: plant genome DNA is extracted using CTAB method；
(3) be sequenced: after the detection of genome DNA sample that step (2) obtains is qualified, with the method for ultrasonication by DNA with
Machine is broken into the segment of 350bp, modifies DNA fragmentation, method of modifying are as follows: carries out end reparation, phosphorylation to DNA fragmentation
And add ploy (A) plus sequence measuring joints；Then it is purified, PCR amplification, constructs sequencing library；Library passes through after quality inspection is qualified
Illumina HiSeqX Ten is sequenced, and carries out quality control to the reads of acquisition；
(4) count with reference to genome alignment: the reads for resurveying sequence acquisition to step (3) is repositioned into reference to gene
In group.BWA software is mainly used for the short sequence that two generation high-flux sequences obtain and the comparison with reference to genome.It is positioned by comparing
Position of the Clean reads on reference genome counts the information such as sequencing depth, the genome coverage of each sample, goes forward side by side
The detection of row variation；
(5) SNP detection and annotation: the detection of SNP mainly uses GATK software realization；Annotation variation (SNP, Small
InDel) and forecast variation influences to carry out using software SnpEff.
(6) SNP-index association analysis: being first filtered SNP, and filter criteria is as follows: having filtered out first multiple
The SNP site of genotype, next filters out SNP site of the reads support less than 4, filters out genotype between mixed pond again
Consistent SNP site and recessive mixed pond gene are not from the SNP site of recessive parent；Utilize SNP-index method meter
Relating value is calculated, and △ SNP-index is fitted using DISTANCE method.The SNP-index and △ of two mixed ponds respectively
The distribution of SNP-index.
(7) candidate interval analysis: as shown in Figure 1, the genomic region more than corresponding threshold value of 95% confidence interval of selection, it should
Genomic region is located on the 1st chromosome of rice in the section 26.57Mb-31.55Mb；We utilize paddy gene in this section of region
Group annotation website MSU-RGAP predicted gene annotation, candidate region variant sites functional annotation, candidate gene expression analysis etc. but
Do not find candidate gene；It is further analyzed, as shown in Fig. 2, the upstream 19.73- in the section 26.57Mb-31.55Mb
SNP quantity declines suddenly in the region 26.50Mb, this may be the major reason for causing the candidate region BSA-seq inaccuracy, because
This, it is candidate regions that we, which select its upstream region 19.73-26.50Mb, is predicted using rice genome annotation website MSU-RGAP
Gene annotation, candidate region variant sites functional annotation, candidate gene expression analysis etc. obtain rice seed ginned cotton pigment synthesis base
The candidate gene LOC_Os01g44260 of cause.
The present embodiment has also been substantially carried out following quality with annotation to SNP detection and has controlled:
Step S1: snp and indel is obtained with reference to genome based on rice, the specific method is as follows: SNP (Single
Nucleotide Polymorphism, single nucleotide polymorphism) and small InDel (small Insertion and
Deletion, the insertion and missing of small fragment) detection mainly use GATK software tool pack to realize.By bwa software, take
The sequencing reads of high quality is compared to rice and is referred to genome by mem algorithm, according to Clean reads in reference genome
Positioning result filters redundancy reads (MarkDuplicates) using Picard, to guarantee the accuracy of testing result.Then
It is detected using the variation that HaplotypeCaller (the local haplotype assembling) algorithm of GATK carries out SNP and InDel, each sample
Each self-generating gVCF of this elder generation, then carry out group joint-genotype and obtain variant sites collection.In order to guarantee make a variation result can
By property, the result that makes a variation passes through stringent filtering, and main filtration parameter is as follows:
1. the variation quantity in 5bp window should not be more than 2；
2. QUAL < 30, (QUAL are as follows: the mass value of Phred format indicates that there are the possibility that variant makes a variation in the site
Property).
Mass value then filtering out lower than 30；
3. QD < 2.0, (QD are as follows: the ratio that variation mass value is obtained divided by overburden depth, overburden depth is on this site
All the sum of overburden depths of sample containing variation base).QD then filtering out lower than 2.0；
4. MQ < 40, (MQ are as follows: all to compare to the root mean square of the comparison mass value of the reads on the site).MQ is lower than 40
Then filter out；
5. FS > 60, (FS are as follows: the value converted by the p-value that Fisher is examined describes to be sequenced or compare
Clock synchronization whether there is apparent positive minus strand for containing only the reads of variation and containing only the reads of reference sequences base
Specificity).That is, being not in the special comparison result of chain, FS should be close to zero.FS then filtering out higher than 60；
6. the default value processing that other variation filtration parameters are specified using GATK official.
Step S2: the snp list strictly filtered obtained based on step S1 is obtained by the script of customization in male parent pond
And it is the site snp between parent that maternal pond, which has discrepant site, and the distribution density of snp is then counted by sliding window, is led to
It crosses the script customized and draws distribution map.
In conclusion it is accurate to carry out for the small genome area of difference to candidate gene using the present processes
Prediction, and method of the invention also has quick, efficient, cheap advantage.
The embodiments described above only express several embodiments of the present invention, and the description thereof is more specific and detailed, but simultaneously
Limitation of the scope of the invention therefore cannot be interpreted as.It should be pointed out that for those of ordinary skill in the art,
Without departing from the inventive concept of the premise, various modifications and improvements can be made, these belong to protection model of the invention
It encloses.Therefore, protection scope of the present invention should be determined by the appended claims.
Claims (9)
1. a kind of method of low-density SNP genome area Accurate Prediction BSA-seq candidate gene, which is characterized in that the side
Method includes the following steps:
(1) mix pond: the significant parent of selection target Traits change constructs segregating population, and extreme table is then selected from segregating population
Several single plants of type are mixed into the pond DNA of two equivalent respectively；
(2) it extracts DNA: extracting plant genome DNA；
(3) be sequenced: the DNA sample of detecting step (2), it is qualified after by DNA fragmentation, DNA fragmentation is modified, PCR amplification,
Sequencing library is constructed, is sequenced after library quality inspection is qualified；
(4) it compares: the sequencing reads that step (3) obtain being repositioned into reference on genome, being compared, counting, is calculated
Sequencing depth and coverage relative to reference genome；
(5) detection of SNP SNP detection and annotation: is carried out using GATK software；Annotation variation and pre- is carried out using software SnpEff
Survey variation；
(6) SNP-index association analysis: being filtered SNP, carries out frequency difference analysis, SNP-index and △ is calculated
The distribution of SNP-index；
(7) candidate interval analysis: according to the distribution situation of step (6) △ SNP-index, select density regions for candidate regions
Between, candidate section gene is annotated using genome annotation website；Functional annotation is carried out to candidate section variant sites, is looked for
There is the gene of functional variants out, obtains candidate gene；Candidate gene is verified using qRT-PCR technology.
2. the method for low-density SNP genome area Accurate Prediction BSA-seq candidate gene according to claim 1, special
Sign is that the filter criteria of step (6) the SNP filtering is as follows: firstly, the SNP site of multiple genotype is filtered out,
It is secondary, filter out SNP site of the reads support less than 4, filter out between mixed pond again the consistent SNP site of genotype and
The mixed pond gene of recessiveness is not from the SNP site of recessive parent.
3. the method for low-density SNP genome area Accurate Prediction BSA-seq candidate gene according to claim 1, special
Sign is that the calculating of the step (6) calculates relating value using SNP-index method, and using DISTANCE method to △
SNP-index is fitted.
4. the method for low-density SNP genome area Accurate Prediction BSA-seq candidate gene according to claim 1, special
Sign is that step (5) the SNP detection and annotation method are as follows:
Step S1: SNP the and small InDel of sequencing genomes is detected by GATK software tool pack；By bwa software, adopt
Mem algorithm is taken to compare the sequencing reads of high quality to reference genome, according to Clean reads determining in reference genome
Position is as a result, filter redundancy reads using Picard；The change of SNP and InDel is carried out using the local haplotype packing algorithm of GATK
Different detection, the first each self-generating gVCF of each sample, then carry out group joint-genotype and obtain variant sites collection；And to variation
As a result it is filtered to obtain filtered snp list, the filter criteria are as follows: the variation quantity in 5bp window is no more than 2；
The mass value of Phred format is not less than 30；Variation mass value is not less than 2.0 divided by the ratio of overburden depth；All comparisons extremely should
The root mean square of the comparison mass value of reads on site is not less than 40；FS value is not higher than 60；Other variation filtration parameters use
The specified default value processing of GATK official；
Step S2: obtaining filtered snp list based on step S1, is obtained by the script of customization in male parent pond and maternal pond
Having discrepant site is the site snp between parent, and the distribution density of snp, the foot of customization are then counted by sliding window
This picture distribution map.
5. a kind of application low-density SNP genome area Accurate Prediction BSA-seq as described in claim 1-4 any one is candidate
Application of the method for gene in plant gene label.
6. application according to claim 5, which is characterized in that the plant is rice.
7. application according to claim 6, which is characterized in that the parent of the rice is that Huang Hua is accounted for and Donglan ink rice.
8. application according to claim 5, which is characterized in that the plant gene is that rice seed peel anthocyanidin synthesizes base
Cause.
9. application according to claim 8, which is characterized in that the anthocyanidin synthesis gene is LOC_Os01g44260.
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| CN109698009A (en) * | 2019-03-01 | 2019-04-30 | 华中农业大学 | It is a kind of based on presence/deletion mutation metagenome construction method |
| CN111223520B (en) * | 2019-11-20 | 2023-09-12 | 云南省烟草农业科学研究院 | Whole genome selection model for predicting nicotine content in tobacco and application thereof |
| CN111091873B (en) * | 2019-12-13 | 2023-07-18 | 北京市商汤科技开发有限公司 | Gene mutation recognition method and device, electronic equipment and storage medium |
| CN112226529A (en) * | 2020-09-09 | 2021-01-15 | 广西壮族自治区农业科学院 | SNP molecular marker of wax gourd blight-resistant gene and application |
| CN112652362B (en) * | 2020-11-27 | 2022-08-30 | 山东省农业科学院奶牛研究中心 | Method for screening bovine plateau hypoxia adaptive gene ALDOC and functional molecular marker and application thereof |
| CN112575104A (en) * | 2020-12-11 | 2021-03-30 | 黑龙江省科学院大庆分院 | Method for quickly positioning industrial hemp character related gene |
| CN113284551A (en) * | 2021-04-28 | 2021-08-20 | 中国农业科学院蔬菜花卉研究所 | Method for positioning leaf color character of rosa davurica pall |
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| CN102121046A (en) * | 2009-06-25 | 2011-07-13 | 中国科学院北京基因组研究所 | Chinese population linkage analysis single nucleotide polymorphism (SNP) marker sets and use method and application thereof |
| CN102899315A (en) * | 2011-07-29 | 2013-01-30 | 江汉大学 | Method for sequencing clone genes with recessive mixed pools |
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